Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/12154#discussion_r58756912
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManager.scala
---
@@ -0,0 +1,217 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+
+package org.apache.spark.streaming.scheduler
+
+import scala.util.Random
+
+import org.apache.spark.{ExecutorAllocationClient, SparkConf}
+import org.apache.spark.internal.Logging
+import org.apache.spark.streaming.util.RecurringTimer
+import org.apache.spark.util.{Clock, Utils}
+
+/**
+ * Class that manages executor allocated to a StreamingContext, and
dynamically request or kill
+ * executors based on the statistics of the streaming computation. At a
high level, the policy is:
+ * - Use StreamingListener interface get batch processing times of
completed batches
+ * - Periodically take the average batch completion times and compare with
the batch interval
+ * - If (avg. proc. time / batch interval) >= scaling up ratio, then
request more executors
--- End diff --
Done.
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